Land Surface Temperature and Scaling Factors for Different Satellite Datasets

Land surface parameters are highly integrated and have a direct effect on water and energy balance and weather predictions. Due to the difficulties in correcting the influences of the atmosphere absorbability and the earth surface emissivity diversification, the retrieval of land surface temperature (LST) from satellite data is a challenging task. To retrieve microwave land emissivity, infrared surface skin temperatures have been used as surface physical temperature. However, passive microwave emissions originate from deeper layers with respect to the skin temperature. So, this inconsistency in sensitivity depths between skin temperatures and microwave temperatures may introduce a discrepancy in the determined emissivity. In this research, six sample sites were chosen on the earth for 2013 and 2014 and then land surface temperature from AMSR-2, Landsat and ASTER brightness temperature values have been derived. The algorithm has been developed from a surface brightness temperature dataset, which has used as inputs surface parameters and atmospheric quantities. The retrieved LST has been compared within AMSR-2, Landsat and ASTER for the same period and area. Maximum time ASTER has shown higher temperature than other data and AMSR-2 has lower temperature on same area. Landsat and ASTER is closer to ground measured temperature than AMSR-2 data. It will be interesting to see how the satellite-derived surface temperature will behave in an assimilation scheme in a follow-up study.